A stochastic multi-agent system for Internet of Things-enabled waste management in smart cities

Anagnostopoulos, Theodoros; Zaslavsky, Arkady; Sosunova, Inna; Fedchenkov, Petr; Medvedev, Alexey; Ntalianis, Klimis; Skourlas, Christos; Rybin, A. V.; Khoruznikov, Sergei

doi:10.1177/0734242x18783843

Cited by 20 publications

(12 citation statements)

References 9 publications

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“…The following research directions were considered during the research: 1) city-level SWM systems, 2) SGBs and SWM systems with SGB-related services, 3) stakeholders in SWM systems, and 4) information shared between SWM systems and stakeholders. Additionally, we studied the physical infrastructure of SWM systems and 4 Network Analysis Interface for Literature Studies, nailsproject.net 5 KH Coder is a free software for quantitative content analysis or text mining, khcoder.net SWM system implementations. The collected and analyzed data of this extensive literature review are summarized in Section 4 and in the Appendix.…”

Section: Discussionmentioning

confidence: 99%

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IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review

Sosunova

Porras

2022

IEEE Access

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Section: Discussionmentioning

confidence: 99%

“…The use of SWM systems, i.e. the utilization of information and communication technology (ICT) in waste management, will improve the energy efficiency and environmental safety of solid-waste exports, improve citizens' quality of life, and reduce resource consumption [5].…”

Section: Introductionmentioning

confidence: 99%

IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review

Sosunova

Porras

2022

IEEE Access

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“…For possible future research directions, locational decisions of the required facilities such as waste bins and disposal facilities and more decision criteria can be considered in the proposed model such as environmental and social objectives to design a more sustainable waste collection system. Moreover, other uncertainty methods can be investigated including fuzzy theory (Tirkolaee et al, 2019b), stochastic programming (Anagnostopoulos et al, 2018), grey systems (Pai et al, 2011), etc.…”

Section: Discussionmentioning

confidence: 99%

A robust bi-objective multi-trip periodic capacitated arc routing problem for urban waste collection using a multi-objective invasive weed optimization

et al. 2019

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Urban waste collection is one of the principal processes in municipalities with large expenses and laborious operations. Among the important issues raised in this regard, the lack of awareness of the exact amount of generated waste makes difficulties in the processes of collection, transportation and disposal. To this end, investigating the waste collection issue under uncertainty can play a key role in the decision-making process of managers. This paper addresses a novel robust bi-objective multi-trip periodic capacitated arc routing problem under demand uncertainty to treat the urban waste collection problem. The objectives are to minimize the total cost (i.e. traversing and vehicles’ usage costs) and minimize the longest tour distance of vehicles (makespan). To validate the proposed bi-objective robust model, the ε-constraint method is implemented using the CPLEX solver of GAMS software. Furthermore, a multi-objective invasive weed optimization algorithm is then developed to solve the problem in real-world sizes. The parameters of the multi-objective invasive weed optimization are tuned optimally using the Taguchi design method to enhance its performance. The computational results conducted on different test problems demonstrate that the proposed algorithm can generate high-quality solutions considering three indexes of mean of ideal distance, number of solutions and central processing unit time. It is proved that the ε-constraint method and multi-objective invasive weed optimization can efficiently solve the small- and large-sized problems, respectively. Finally, a sensitivity analysis is performed on one of the main parameters of the problem to study the behavior of the objective functions and provide the optimal policy.

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“…The objective of the proposed optimization model is to minimize the total transportation cost while maximizing the recovery of value still embedded in waste bins. A multi-agent system is incorporated in (Anagnostopoulos et al, 2018) for IoT-enabled waste management to stochastically reassign trucks to collect waste from bins through time in smart cities.…”

Section: Waste Management For Smart Cities: State Of the Artmentioning

confidence: 99%

IoT-enabled tip and swap waste management models for smart cities

Anagnostopoulos¹,

Zaslavsky²,

Ntalianis³

et al. 2021

IJEWM

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Current technical advances in sensors, actuators, and wireless networks enable the Internet of Things (IoT) technology. Key features of IoT are the 'smart things', which have significant computational capabilities. In this paper we focus on waste management using dynamic allocation of collection and transfer points with subsequent transporting of waste to processing facilities. Waste management involves a variety of tasks from the collection of the waste in the field to the transport and disposal to the appropriate locations. The proposed waste management system contributes to innovative Smart City (SC) applications with impact in the dynamic allocation management of mobile depots in the SC. We propose a set of models, which advocate for replacing traditional way of tipping waste into larger containers by swapping full waste bins with empty ones. We also propose the concept of mobile depots as intermediate collection and transfer points. Quantitative and qualitative metrics to assess the efficiency of the proposed models are used. We incorporate the CT, TT, L, D and F quantitative metrics and the S qualitative metric. The S metric takes as input the values of the quantitative metrics and gives an output of high or low satisfaction. The models demonstrate their efficiency and potential adoption by SCs.

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A stochastic multi-agent system for Internet of Things-enabled waste management in smart cities

Cited by 20 publications

References 9 publications

IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review

IoT-Enabled Smart Waste Management Systems for Smart Cities: A Systematic Review

A robust bi-objective multi-trip periodic capacitated arc routing problem for urban waste collection using a multi-objective invasive weed optimization

IoT-enabled tip and swap waste management models for smart cities

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